Emotion recognition with convolutional neural network and EEG-based EFDMs
Electroencephalogram (EEG), as a direct response to brain activity, can be used to detect
mental states and physical conditions. Among various EEG-based emotion recognition …
mental states and physical conditions. Among various EEG-based emotion recognition …
Emotion recognition from EEG signal focusing on deep learning and shallow learning techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
EEG-based cross-subject emotion recognition using Fourier-Bessel series expansion based empirical wavelet transform and NCA feature selection method
Automated emotion recognition using brain electroencephalogram (EEG) signals is
predominantly used for the accurate assessment of human actions as compared to facial …
predominantly used for the accurate assessment of human actions as compared to facial …
Cross-subject emotion recognition using flexible analytic wavelet transform from EEG signals
V Gupta, MD Chopda, RB Pachori - IEEE Sensors Journal, 2018 - ieeexplore.ieee.org
Human emotion is a physical or psychological process which is triggered either consciously
or unconsciously due to perception of any object or situation. The electroencephalogram …
or unconsciously due to perception of any object or situation. The electroencephalogram …
Emotion recognition for human-robot interaction: Recent advances and future perspectives
A fascinating challenge in the field of human–robot interaction is the possibility to endow
robots with emotional intelligence in order to make the interaction more intuitive, genuine …
robots with emotional intelligence in order to make the interaction more intuitive, genuine …
Differences first in asymmetric brain: A bi-hemisphere discrepancy convolutional neural network for EEG emotion recognition
Neuroscience research studies have shown that the left and right hemispheres of the human
brain response differently to the same or different emotions. Exploiting this difference in the …
brain response differently to the same or different emotions. Exploiting this difference in the …
Utilizing deep learning towards multi-modal bio-sensing and vision-based affective computing
TP Jung, TJ Sejnowski - IEEE Transactions on Affective …, 2019 - ieeexplore.ieee.org
In recent years, the use of bio-sensing signals such as electroencephalogram (EEG),
electrocardiogram (ECG), etc. have garnered interest towards applications in affective …
electrocardiogram (ECG), etc. have garnered interest towards applications in affective …
Affective image content analysis: Two decades review and new perspectives
Images can convey rich semantics and induce various emotions in viewers. Recently, with
the rapid advancement of emotional intelligence and the explosive growth of visual data …
the rapid advancement of emotional intelligence and the explosive growth of visual data …
A novel bi-hemispheric discrepancy model for EEG emotion recognition
Neuroscience study has revealed the discrepancy of emotion expression between the left
and right hemispheres of human brain. Inspired by this study, in this article, we propose a …
and right hemispheres of human brain. Inspired by this study, in this article, we propose a …
Domain adaptation for EEG emotion recognition based on latent representation similarity
Emotion recognition has many potential applications in the real world. Among the many
emotion recognition methods, electroencephalogram (EEG) shows advantage in reliability …
emotion recognition methods, electroencephalogram (EEG) shows advantage in reliability …